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Measuring Noise in Inventory Models

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  • Steven N. Durlauf
  • Louis J. Maccini

Abstract

This paper has two purposes. One is to assess different models of inventory behavior in terms of their ability to well approximate the realized data on inventories. We do this initially for the pure production smoothing model and then for a sequence of generalizations of the model. Our analysis both performs specification tests as well as measures the deviations of the data from each null model, which we refer to as model noise. This involves the introduction of a noise ratio which provides a metric for measuring the magnitude of the noise component of the data. A second purpose is to explore whether observed cost shocks, including in particular carefully measured series on raw materials prices, can be helpful in explaining inventory movements. We find that the basic production level smoothing model of inventories, augmented by buffer stock motives, observed cost shocks, properly measured, and to a lesser extent stockout avoidance motives, appears to well approximate monthly inventory data.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 4487.

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Date of creation: Oct 1993
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Handle: RePEc:nbr:nberwo:4487

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  1. West, Kenneth D., 1983. "A note on the econometric use of constant dollar inventory series," Economics Letters, Elsevier, vol. 13(4), pages 337-341.
  2. Blinder, Alan S, 1986. "More on the Speed of Adjustment in Inventory Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 18(3), pages 355-65, August.
  3. Olivier J. Blanchard, 1983. "The Production and Inventory Behavior of the American Automobile Industry," NBER Working Papers 0891, National Bureau of Economic Research, Inc.
  4. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  5. Fair, Ray C., 1989. "The production-smoothing model is alive and well," Journal of Monetary Economics, Elsevier, vol. 24(3), pages 353-370, November.
  6. Jeffrey Fuhrer & George Moore & Scott Schuh, 1993. "Estimating the linear-quadratic inventory model: maximum likelihood versus generalized method of moments," Finance and Economics Discussion Series 93-11, Board of Governors of the Federal Reserve System (U.S.).
  7. Maccini, Louis J & Rossana, Robert J, 1984. "Joint Production, Quasi-Fixed Factors of Production, and Investement in Finished Goods Inventories," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 16(2), pages 218-36, May.
  8. Kenneth D. West, 1989. "Order Backlogs and Production Smoothing," NBER Working Papers 2385, National Bureau of Economic Research, Inc.
  9. Rossana, Robert J, 1990. "Interrelated Demands for Buffer Stocks and Productive Inputs: Estimates for Two-Digit Manufacturing Industries," The Review of Economics and Statistics, MIT Press, vol. 72(1), pages 19-29, February.
  10. Jeffrey A. Miron & Stephen P. Zeldes, . "Seasonality, Cost Shocks and the Production Smoothing Model of Inventories," Rodney L. White Center for Financial Research Working Papers 01-87, Wharton School Rodney L. White Center for Financial Research.
  11. Martin S. Eichenbaum, 1990. "Some Empirical Evidence on the Production Level and Production Cost Smoothing Models of Inventory Investment," NBER Working Papers 2523, National Bureau of Economic Research, Inc.
  12. Gertler, M. & Gilchrist, S., 1992. "Monetary Policy, Business Cycles and the Behavior of Small Manufacturing Firms," Working Papers 92-08, C.V. Starr Center for Applied Economics, New York University.
  13. Ramey, Valerie A, 1991. "Nonconvex Costs and the Behavior of Inventories," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 306-34, April.
  14. Kenneth D. West, 1993. "Inventory Models," NBER Technical Working Papers 0143, National Bureau of Economic Research, Inc.
  15. Ghali, Moheb A, 1987. "Seasonality, Aggregation and the Testing of the Production Smoothing Hypothesis," American Economic Review, American Economic Association, vol. 77(3), pages 464-69, June.
  16. Kenneth D. West, 1985. "A Variance Bounds Test of the Linear Quardractic Inventory Model," NBER Working Papers 1581, National Bureau of Economic Research, Inc.
  17. Alan S. Blinder & Louis J. Maccini, 1990. "The Resurgence of Inventory Research: What Have We Learned?," NBER Working Papers 3408, National Bureau of Economic Research, Inc.
  18. Spencer Krane & Steven Braun, 1990. "Production smoothing evidence from physical-product data," Working Paper Series / Economic Activity Section 103, Board of Governors of the Federal Reserve System (U.S.).
  19. Kahn, James A, 1992. "Why Is Production More Volatile Than Sales? Theory and Evidence on the Stockout-Avoidance Motive for Inventory-Holding," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 481-510, May.
  20. Alan S. Blinder & Louis J. Maccini, 1991. "Taking Stock: A Critical Assessment of Recent Research on Inventories," Journal of Economic Perspectives, American Economic Association, vol. 5(1), pages 73-96, Winter.
  21. Kenneth D. West & David W. Wilcox, 1993. "Some evidence on finite sample behavior of an instrumental variables estimator of the linear quadratic inventory model," Finance and Economics Discussion Series 93-29, Board of Governors of the Federal Reserve System (U.S.).
  22. Haltiwanger, John C. & Maccini, Louis J., 1989. "Inventories, orders, temporary and permanent layoffs: An econometric analysis," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 30(1), pages 301-366, January.
  23. Eichenbaum, Martin, 1983. "A rational expectations equilibrium model of inventories of finished goods and employment," Journal of Monetary Economics, Elsevier, vol. 12(2), pages 259-277.
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